diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..4a1ff58c3a633f51533d402e7316cd7819fb711e
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,6 @@
+.idea
+__pycache__
+pages/application/DecisionTree/utils/__pycache__
+pages/application/DecisionTree/__pycache__
+pages/application/__pycache__
+decision_tree_classifier_20170212.pkl
\ No newline at end of file
diff --git a/app.py b/app.py
index 41455d2f594c8664b14f6dc32b539b96a2f3cac3..e605e68bf0922f4f6ca56198ba817b533d2ddd50 100644
--- a/app.py
+++ b/app.py
@@ -1,19 +1,15 @@
# Run this app with `python app.py` and
# visit http://127.0.0.1:8050/ in your web browser.
+import json
+
import dash
-import json
-from dash import dcc
-from dash import html
-from dash import dcc, html, Input, Output, State
import dash_bootstrap_components as dbc
+import pandas as pd
+from dash import Input, Output, State, dcc, html
from dash.exceptions import PreventUpdate
from pages.application.layout_application import Model, View
-from utils import parse_contents_instance, parse_contents_tree, extract_data
-
-import base64
-import io
-import pandas as pd
+from utils import extract_data, parse_contents_instance, parse_contents_tree
'''
Loading data
@@ -44,7 +40,7 @@ app.layout = html.Div([
Callback for the app
'''
@app.callback(
- Output('tree_filename', 'children'),
+ Output('dataset_filename', 'children'),
Output('instance_filename', 'children'),
Output('graph', 'children'),
Output('explanation', 'children'),
@@ -64,14 +60,14 @@ def update_ml_type(value_ml_model, dataset_contents, instance_contents, enum, xt
ihm_id = ctx.triggered[0]['prop_id'].split('.')[0]
if ihm_id == 'ml_model_choice' :
model.update_ml_model(value_ml_model)
- return dataset_filename, instance_filename, "", ""
+ return "", "", "", ""
elif ihm_id == 'ml_dataset_choice':
if value_ml_model == None :
raise PreventUpdate
- tree = parse_contents_tree(dataset_contents, dataset_filename)
- model.update_dataset(tree)
- return dataset_filename, instance_filename, model.component.network, ""
+ tree, typ = parse_contents_tree(dataset_contents, dataset_filename)
+ model.update_dataset(tree, typ)
+ return dataset_filename, "", model.component.network, ""
elif ihm_id == 'ml_instance_choice' :
if value_ml_model == None or dataset_contents == None or enum == None or xtype==None:
@@ -107,4 +103,4 @@ def update_ml_type(value_ml_model, dataset_contents, instance_contents, enum, xt
Launching app
'''
if __name__ == '__main__':
- app.run_server(debug=True)
\ No newline at end of file
+ app.run_server(debug=True)
diff --git a/pages/application/DecisionTree/DecisionTreeComponent.py b/pages/application/DecisionTree/DecisionTreeComponent.py
index 15f1d2c30f88a199b49f8e79146f82a7f2df4551..6ecb24cc60ae38cd71145b53532efda8f1f0afdb 100644
--- a/pages/application/DecisionTree/DecisionTreeComponent.py
+++ b/pages/application/DecisionTree/DecisionTreeComponent.py
@@ -8,9 +8,12 @@ from os import path
class DecisionTreeComponent():
- def __init__(self, tree):
+ def __init__(self, tree, typ_data):
- self.dt = DecisionTree(from_string = tree)
+ if typ_data == "dt" :
+ self.dt = DecisionTree(from_dt = tree)
+ elif typ_data == "pkl" :
+ self.dt = DecisionTree(from_pickle = tree)
dot_source = visualize(self.dt)
diff --git a/pages/application/DecisionTree/utils/dtree.py b/pages/application/DecisionTree/utils/dtree.py
index db322142bb6ffac20ecf660b7c5ac5290d16072c..ad48a393c16c041dc26fe059eb7b4ae5101280b3 100644
--- a/pages/application/DecisionTree/utils/dtree.py
+++ b/pages/application/DecisionTree/utils/dtree.py
@@ -22,6 +22,8 @@ try: # for Python2
from cStringIO import StringIO
except ImportError: # for Python3
from io import StringIO
+from sklearn.tree import _tree
+import numpy as np
#
#==============================================================================
@@ -30,13 +32,16 @@ class Node():
Node class.
"""
- def __init__(self, feat='', vals=[]):
+ def __init__(self, feat='', vals=[], threshold=None):
"""
Constructor.
"""
self.feat = feat
- self.vals = vals
+ if threshold is not None :
+ self.threshold = threshold
+ else :
+ self.vals = vals
#
@@ -46,14 +51,13 @@ class DecisionTree():
Simple decision tree class.
"""
- def __init__(self, from_file=None, from_fp=None, from_string=None,
- mapfile=None, medges=False, verbose=0):
+ def __init__(self, from_dt=None, from_pickle=None,
+ mapfile=None, verbose=0):
"""
Constructor.
"""
self.verbose = verbose
- self.medges = medges and mapfile != None
self.nof_nodes = 0
self.nof_terms = 0
@@ -70,12 +74,10 @@ class DecisionTree():
OHEMap = collections.namedtuple('OHEMap', ['dir', 'opp'])
self.ohmap = OHEMap(dir={}, opp={})
- if from_file:
- self.from_file(from_file)
- elif from_string:
- self.from_string(from_string)
- elif from_fp:
- self.from_fp(from_fp)
+ if from_dt:
+ self.from_dt(from_dt)
+ elif from_pickle:
+ self.from_pickle_file(from_pickle)
if mapfile:
self.parse_mapping(mapfile)
@@ -84,15 +86,76 @@ class DecisionTree():
for v in self.fdoms[f]:
self.fvmap[tuple([f, v])] = '{0}={1}'.format(f, v)
- if self.medges:
- self.convert_to_multiedges()
+ #problem de feature names et problem de vals dans node
+ def from_pickle_file(self, tree):
+ tree_ = tree.tree_
+ try:
+ feature_names = tree.feature_names_in_
+ except:
+ print("You did not dump the model with the features names")
+ feature_names = [str(i) for i in range(tree.n_features_in_)]
- def from_fp(self, fp):
+ class_names = tree.classes_
+
+ self.nodes = collections.defaultdict(lambda: Node(feat='', vals={}))
+ self.terms={}
+ self.nof_nodes = tree_.node_count
+ self.nof_terms = 0
+ self.root_node = 0
+
+ feature_name = [
+ feature_names[i] if i != _tree.TREE_UNDEFINED else "undefined!"
+ for i in tree_.feature]
+
+ def recurse(feats, fdoms, node):
+ if tree_.feature[node] != _tree.TREE_UNDEFINED:
+ name = feature_name[node]
+ val = tree_.threshold[node]
+
+ #faire une boucle for des vals ?
+ self.nodes[int(node)].feat = name
+ self.nodes[int(node)].vals[int(np.round(val,4))] = int(tree_.children_left[node])
+
+ self.nodes[int(node)].feat = name
+ self.nodes[int(node)].vals[int(4854)] = int(tree_.children_right[node])
+
+ feats.add(name)
+ fdoms[name].add(int(np.round(val,4)))
+ feats, fdoms = recurse(feats, fdoms, tree_.children_left[node])
+ fdoms[name].add(4854)
+ feats, fdoms = recurse(feats, fdoms, tree_.children_right[node])
+
+ else:
+ self.terms[node] = class_names[np.argmax(tree_.value[node])]
+ print("leaf {}".format(tree_.value[node]))
+
+ return feats, fdoms
+
+ self.feats, self.fdoms = recurse(set([]), collections.defaultdict(lambda: set([])), self.root_node)
+
+ for parent in self.nodes:
+ conns = collections.defaultdict(lambda: set([]))
+ for val, child in self.nodes[parent].vals.items():
+ conns[child].add(val)
+ self.nodes[parent].vals = {frozenset(val): child for child, val in conns.items()}
+
+ self.feats = sorted(self.feats)
+ self.feids = {f: i for i, f in enumerate(self.feats)}
+ self.fdoms = {f: sorted(self.fdoms[f]) for f in self.fdoms}
+ self.nof_terms = len(self.terms)
+ self.nof_feats = len(self.feats)
+
+ self.paths = collections.defaultdict(lambda: [])
+ self.extract_paths(root=self.root_node, prefix=[])
+
+ def from_dt(self, data):
"""
Get the tree from a file pointer.
"""
- lines = fp.readlines()
+ contents = StringIO(data)
+
+ lines = contents.readlines()
# filtering out comment lines (those that start with '#')
lines = list(filter(lambda l: not l.startswith('#'), lines))
@@ -149,13 +212,6 @@ class DecisionTree():
self.paths = collections.defaultdict(lambda: [])
self.extract_paths(root=self.root_node, prefix=[])
- def from_string(self, string):
- """
- Get a DT from a string.
- """
-
- self.from_fp(StringIO(string))
-
def extract_paths(self, root, prefix):
"""
Traverse the tree and extract explicit paths.
diff --git a/pages/application/layout_application.py b/pages/application/layout_application.py
index 59efb81b1a4f12606d9dabfd806adb5056ceba51..78c5c019436a0e3ac2a5e74ea59434b872b586f6 100644
--- a/pages/application/layout_application.py
+++ b/pages/application/layout_application.py
@@ -20,6 +20,7 @@ class Model():
self.ml_model = ''
self.dataset = ''
+ self.typ_data = ''
self.instance = ''
@@ -29,11 +30,12 @@ class Model():
def update_ml_model(self, ml_model_update):
self.ml_model = ml_model_update
self.component_class = self.dict_components[self.ml_model]
+ self.component_class = globals()[self.component_class]
- def update_dataset(self, dataset_update):
+ def update_dataset(self, dataset_update, typ_data):
self.dataset = dataset_update
- self.component_class = globals()[self.component_class]
- self.component = self.component_class(self.dataset)
+ self.typ_data = typ_data
+ self.component = self.component_class(self.dataset, self.typ_data)
def update_instance(self, instance, enum, xtype, solver="g3"):
self.instance = instance
@@ -64,7 +66,7 @@ class View():
'margin': '10px'
}
),
- html.Div(id='tree_filename')])
+ html.Div(id='dataset_filename')])
self.instance_upload = html.Div([
dcc.Upload(
diff --git a/utils.py b/utils.py
index dcdf87631f5cb067c89fb201da501c5c6eaad55c..4b194caae78a7169bce243b206beb8ecee45789a 100644
--- a/utils.py
+++ b/utils.py
@@ -1,25 +1,28 @@
-import dash
-import json
-from dash import html
-from dash import dcc
-import dash_bootstrap_components as dbc
-
import base64
import io
+import pickle
import pandas as pd
+import sklearn
+from dash import html
+
def parse_contents_tree(contents, filename):
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
- try:
- data = decoded.decode('utf-8')
+ try:
+ if '.dt' in filename:
+ data = decoded.decode('utf-8')
+ typ = 'dt'
+ elif '.pkl' in filename:
+ data = pickle.load(io.BytesIO(decoded))
+ typ = 'pkl'
except Exception as e:
print(e)
return html.Div([
'There was an error processing this file.'
])
- return data
+ return data, typ
def parse_contents_instance(contents, filename):
content_type, content_string = contents.split(',')
@@ -49,4 +52,4 @@ def extract_data(data):
ml_type = data[i]['ml_type']
dict_components[ml_type] = data[i]['component']
- return names_models, dict_components
\ No newline at end of file
+ return names_models, dict_components